Big data shows how ambient temperature can have clinical implications

When you go to the doctor for a medical exam, or to get your blood drawn, doctors are running tests and considering many factors occurring within the body. However, it’s not always apparent how the environment’s ambient temperature—or  room temperature—influences the results of some of the most common laboratory tests, like blood work or lipid tests.

Lab tests measure important parts of patient physiology, but they can vary for distinctive reasons. A new study, “Variation in common laboratory test results due to ambient temperature,” by Ziad Obermeyer,  Blue Cross Distinguished Assistant Professor at Berkeley Public Health, and Devin Pope of the University of Chicago, examines an often overlooked source of variation in lab tests: how day-to-day temperature fluctuations affect lab test results, over and above seasonal variations and the patients’ average body temperature.

In a sample of more than four million patients modeling two million test results, the researchers found that ambient temperatures affected more than 90% of individual tests and 51 of 75 assays—tests of metal ores inside the body—including measures of kidney function, cellular blood components, and lipids such as cholesterol and triglycerides. “It’s important to note that these changes were small: less than one percent differences in most tests under normal temperature conditions,” Obermeyer says.

While the fluctuations in ambient temperature were generally small, the study concluded that medical professionals should adjust for temperature when reporting lab results to account for day-to-day variabilities.

“This is exactly the kind of pattern that doctors might miss,” says Ziad Obermeyer. “We’re not looking for it, and lab tests are noisy.”

Doing so could reduce weather-related variability at a lower cost than new laboratory assay technology or investments in temperature control in transport vans. In practice, decisions on adjustment would need to be at the discretion of the laboratory staff and the treating physician, potentially on a case-by-case basis. According to the authors, the study may also have broader clinical implications.

“The textbook way of thinking about medical research is bench to bedside. First, we come up with a hypothesis, based on theory, then we test it with data,” Obermeyer says. “As more and more big data comes online, like the massive dataset of lab tests we used, we can flip that process on its head: discover fascinating new patterns and then use bench science to get to the bottom of it. I think this bedside-to-bench model is just as important as its better-known cousin because it can open up totally new questions in human physiology.”